Automated Systems for Calculating Arteriovenous Ratio in Retinographies : A Scoping Review

There is evidence of an association between hypertension and retinal arteriolar narrowing. Manual measurement of retinal vessels comes with additional variability, which can be eliminated using automated software. This scoping review aims to summarize research on automated retinal vessel analysis systems. Searches were performed on Medline, Scopus, and Cochrane to find studies examining automated systems for the diagnosis of retinal vascular alterations caused by hypertension using the following keywords: diagnosis; diagnostic screening programs; image processing, computer-assisted; artificial intelligence; electronic data processing; hypertensive retinopathy; hypertension; retinal vessels; arteriovenous ratio and retinal image analysis. The searches generated 433 articles. Of these, 25 articles published from 2010 to 2022 were included in the review. The retinographies analyzed were extracted from international databases and real scenarios. Automated systems to detect alterations in the retinal vasculature are being introduced into clinical practice for diagnosis in ophthalmology and other medical specialties due to the association of such changes with various diseases. These systems make the classification of hypertensive retinopathy and cardiovascular risk more reliable. They also make it possible for diagnosis to be performed in primary care, thus optimizing ophthalmological visits

Relationship between Retinal Microvasculature, Cardiovascular Risk and Silent Brain Infarction in Hypertensive Patients

Risc cardiovascular; Hipertensió; Microvasculatura retinianaRiesgo cardiovascular; Hipertensión; Microvasculatura retinianaCardiovascular risk; Hypertension; Retinal microvasculatureObjective: The aims of this study are to analyze the role of artery-vein ratio AVR assessment using VesselMap 2 software (Imedos Systems) and cardiovascular risk evaluation by means of REGICOR in the prediction of silent brain infarction (SBI) in middle-age hypertensive patients from the ISSYS study. Material and Methods: A cross-sectional study with 695 patients with hypertension aged 50 to 70 years who participated in the project Investigating Silent Strokes in HYpertensives: a Magnetic Resonance Imaging Study (ISSYS), was conducted in two Primary Care Centres of Barcelona. Participants agreed to a retinography and an MRI to detect silent brain infarction (SBI). The IMEDOS software was used for the semiautomatic caliber measurement of retinal arteries and veins, and the AVR was considered abnormal when <0.66. The REGICOR score was calculated for all patients. Results: Multivariate logistic regression analysis was used to evaluate the impact of AVR and REGICOR scores on SBI. The OR (odds ratio) for a high REGICOR score and an abnormal AVR were 3.16 and 4.45, respectively. When analysing the interaction of both factors, the OR of an abnormal AVR and moderate REGICOR score was 3.27, whereas with a high REGICOR score it reached 13.07. Conclusions: The measurement of AVR in patients with hypertension and with a high REGICOR score can contribute to the detection of silent brain infarction.This project was co-funded by the Basque Government and the European Regional Development Fund

Relationship between Retinal Microvasculature, Cardiovascular Risk and Silent Brain Infarction in Hypertensive Patients

Objective: The aims of this study are to analyze the role of artery-vein ratio AVR assessment using VesselMap 2 software (Imedos Systems) and cardiovascular risk evaluation by means of REGICOR in the prediction of silent brain infarction (SBI) in middle-age hypertensive patients from the ISSYS study. Material and Methods: A cross-sectional study with 695 patients with hypertension aged 50 to 70 years who participated in the project Investigating Silent Strokes in HYpertensives: a Magnetic Resonance Imaging Study (ISSYS), was conducted in two Primary Care Centres of Barcelona. Participants agreed to a retinography and an MRI to detect silent brain infarction (SBI). The IMEDOS software was used for the semiautomatic caliber measurement of retinal arteries and veins, and the AVR was considered abnormal when <0.66. The REGICOR score was calculated for all patients. Results: Multivariate logistic regression analysis was used to evaluate the impact of AVR and REGICOR scores on SBI. The OR (odds ratio) for a high REGICOR score and an abnormal AVR were 3.16 and 4.45, respectively. When analysing the interaction of both factors, the OR of an abnormal AVR and moderate REGICOR score was 3.27, whereas with a high REGICOR score it reached 13.07. Conclusions: The measurement of AVR in patients with hypertension and with a high REGICOR score can contribute to the detection of silent brain infarction

Intelligent Models in Complex Problem Solving

Artificial Intelligence revived in the last decade. The need for progress, the growing processing capacity and the low cost of the Cloud have facilitated the development of new, powerful algorithms. The efficiency of these algorithms in Big Data processing, Deep Learning and Convolutional Networks is transforming the way we work and is opening new horizons

Learning AI with deepint.net

This keynote will examine the evolution of intelligent computer systems over the last years, underscoring the need for human capital in this field, so that further progress can be made. In this regard, learning about AI through experience is a big challenge, but it is possible thanks to tools such as deepint.net, which enable anyone to develop AI systems; knowledge of programming is no longer necessary

Managing smart cities with deepint.net

In this keynote, the evolution of intelligent computer systems will be examined. The need for human capital will be emphasised, as well as the need to follow one’s “gut instinct” in problem-solving. We will look at the benefits of combining information and knowledge to solve complex problems and will examine how knowledge engineering facilitates the integration of different algorithms. Furthermore, we will analyse the importance of complementary technologies such as IoT and Blockchain in the development of intelligent systems. It will be shown how tools like "Deep Intelligence" make it possible to create computer systems efficiently and effectively. "Smart" infrastructures need to incorporate all added-value resources so they can offer useful services to the society, while reducing costs, ensuring reliability and improving the quality of life of the citizens. The combination of AI with IoT and with blockchain offers a world of possibilities and opportunities

AIoT for Smart territories

Artificial Intelligence revived in the last decade. The need for progress, the growing processing capacity and the low cost of the Cloud have facilitated the development of new, powerful algorithms. The efficiency of these algorithms in Big Data processing, Deep Learning and Convolutional Networks is transforming the way we work and is opening new horizons. Thanks to them, we can now analyse data and obtain unimaginable solutions to today’s problems. Nevertheless, our success is not entirely based on algorithms, it also comes from our ability to follow our “gut” when choosing the best combination of algorithms for an intelligent artefact. It's about approaching engineering with a lot of knowledge and tact. This involves the use of both connectionist and symbolic systems, and of having a full understanding of the algorithms used. Moreover, to address today’s problems we must work with both historical and real-time data

DeepTech – AI-IoT in smart cities

In this keynote, the evolution of intelligent computer systems will be examined. The need for human capital will be emphasised, as well as the need to follow one’s “gut instinct” in problem-solving. We will look at the benefits of combining information and knowledge to solve complex problems and will examine how knowledge engineering facilitates the integration of different algorithms. Furthermore, we will analyse the importance of complementary technologies such as IoT and Blockchain in the development of intelligent systems. It will be shown how tools like "Deep Intelligence" make it possible to create computer systems efficiently and effectively. "Smart" infrastructures need to incorporate all added-value resources so they can offer useful services to the society, while reducing costs, ensuring reliability and improving the quality of life of the citizens. The combination of AI with IoT and with blockchain offers a world of possibilities and opportunities

The role of the AIoT and deepint.net

AIoT is a term, also known as intelligence of things, which refers to the new wave of the future of technology that combines two major platforms, very present in today's market: Artificial Intelligence (AI) and the Internet of things (IoT). As IoT devices will generate large amounts of data, Artificial Intelligence is going to be functionally necessary to deal with these huge volumes if we are to have any chance of making sense of the data. This whole process will be called connected intelligence. To take this step forward and definitively enter the era of Intelligence of Things, we will need to enable to a greater or lesser part these cognitive and executive capacities towards objects. To do this, we are going to talk more and more about the concept of Edge Computing (or “edge computing”), which is nothing more than the ability to process data, analyze situations, evaluate possible scenarios and make decisions from the object itself and not from a server hundreds or thousands of miles away

Efficient Deployment of DeepTech AI Models in Engineering Solutions

The blockchain system, appeared in 2009 together with the virtual currency bitcoin, is a record of digital transactions based on a huge database in which all financial operations carried out with electronic currency are registered. The Blockchain (or chain of blocks) is a shared database that works as a book for the record of purchase-sale operations or any other transaction. It is the technological base of the operation of bitcoin, for example. It consists of a set of notes that are in a shared online database in which operations, quantities, dates and participants are registered by means of codes. By using cryptographic keys and being distributed by many computers (people), it presents security advantages against manipulation and fraud. A modification in one of the copies would be useless, but the change must be made in all the copies because the database is open and public